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As detailed in the January 16 JAMA Neurology, scientists led by Beate Ritz of the University of California, Los Angeles, derived a polygenic risk scale for Parkinson’s disease based on 23 known genetic risk factors. They report that higher scores predicted faster cognitive and motor decline during the study’s five-year follow up. The results suggest that genes for PD susceptibility play a role in progression of the disease and that the polygenic risk scores might be valuable prognostic markers.

“This study highlights the influence of common genetic variants and of the polygenic architecture on the variability of disease progression rate in PD,” wrote David Crosiers, University of Antwerp, Belgium, to Alzforum. He noted the need for replication with larger sample sizes and longer follow-up, as well as careful clinical characterization of patients. Crosiers was not involved in the study.

A group led by Mathias Toft, University of Oslo, Norway, previously constructed a polygenic risk score (PRS) for PD based on 19 risk variants (Pihlstrøm et al., 2016). The researchers found that a higher score predicted a shorter time from diagnosis to stage 3 on the Hoehn & Yahr scale, marking the transition from mild to moderate motor dysfunction and the onset of balance problems. However, Toft and colleagues did not measure cognitive change.

Genome-wide association analysis has identified a total of 26 single-nucleotide polymorphisms associated with PD (Jul 2014 news). In the current study, first author Kimberley Paul and colleagues set out to develop a PRS that incorporated the latest GWAS hits. They wanted to confirm the results of the Nordic study and examine whether a PRS could also predict cognitive decline, a common comorbidity in advanced PD.

The group examined data from 285 people of European ancestry who enrolled in UCLA’s Parkinson's Environment and Gene (PEG) study between 2001 and 2007. Subjects averaged 69 years old and all had been diagnosed with PD in the past three years. Over about 5.3 years, 199 came back for up to three follow-up visits. Specialists noted each person’s stage on the Hoehn & Yahr scale and assessed their motor function using the Unified Parkinson’s Disease Rating Scale part III (UPDRS-III). Participants also took the Mini-Mental State Examination (MMSE). The researchers defined cognitive decline as a loss of at least four points on the MMSE over five years and motor decline as a 20-point increase in UPDRS motor score as well as progression to stage 3 of the Hoehn & Yahr.

Paul and colleagues genotyped each volunteer for the 26 PD-associated SNPs. Three SNPs were left out of the final analysis because of inadequate or faulty sequencing. The remaining 23 included variants in LRRK2, MAPT, SNCA, and GBA, all examined previously for links to cognition in PD, though the only strong evidence has been for GBA (Crosiers et al., 2016; Srivatsal et al., 2015; Morley et al., 2012; Guella et al., 2016). The researchers then constructed a PRS for each person based on the number of risk alleles they had, weighted by the estimated effect size of each one (Nalls et al., 2014).

During the follow-up, 32 people developed cognitive decline, while motor symptoms worsened in 41. Ritz and colleagues calculated that for every standard deviation increase in the PRS, cognitive decline and worsening motor control were 44 and 42 percent more likely, respectively, while people were 34 percent more apt to progress to Hoehn & Yahr stage 3. However, the PRS did not predict survival in up to 19 years of passive monitoring for mortality. To make sure GBA variants alone weren’t driving the association between PRS and decline, the scientists reanalyzed the data excluding those loci and came up with largely the same results.

“This is the first study to find that common genetic risk factors [for PD] affect cognitive function,” said Toft. He noted that this is a population-based study, which makes the results more generally relevant. To Clemens Scherzer at Brigham and Women’s Hospital, Boston, this study suggests that multiple loci are likely to drive progression of PD, though he cautioned that dementia and global cognitive impairment were not assessed. Scherzer also noted that rare pathogenic GBA variants alone appear to confer a more substantial increase in cognitive risk for patients with PD than the cumulative GWAS-derived common variants included in the PRS. Extensive genotyping of PD patients is needed to capture these alleles, he said.

If genetic risk factors are important for disease course, it might be possible to reanalyze clinical trials with a stratified patient sample, perhaps revealing treatment effects in subgroups with specific genetic makeup, Toft added. Curiously, while the PRS predicted motor and cognitive decline, few patients had both. In other words, PD patients with a certain set of variants declined cognitively, and a different group of people with a different set of variants declined physically. That cognitive and motor outcomes correlated only weakly in this study further supports the idea that PD is a syndrome comprising different subtypes, Toft said.

“With the decreasing cost of genotyping, using a PRS would be relatively cost-effective, quicker, and less invasive than CSF draws, which are poorly predictive anyway,” wrote Thomas Beach, Banner Sun Health Research Institute, Sun City, Arizona, to Alzforum. “This could be useful for selection of faster-declining subjects for clinical trials.” Toft believes the PRS could be improved by adding in recently identified risk loci (Sept 2017 news on Chang et al., 2017), or new ones identified in a GWAS analysis of clinical phenotypes.—Gwyneth Dickey Zakaib

Comments

The subclinical progression and age at onset, as well as clinical progression subsequent to diagnosis of complex age-related neurodegenerative diseases such as PD, is very likely to involve interactions not only between risk genes but also between genes that code for enzymes (e.g. glutathione-S-transferase) involved in the metabolism and detoxification of xenobiotics. The more we understand these complex interactions, the better will be our chances for identifying modifiable factors such as diet, occupation, and lifestyle that can be adjusted with relatively low risk to the patients while slowing subclinical disease progression and thus, delaying onset.

The rate of disease progression among Parkinson’s disease (PD) patients can be highly variable. Genome-wide association studies (GWAS) in PD have largely focused on the identification of risk alleles for PD and onset age. However, the identification of genetic factors influencing the rate of disease progression could have an important clinical relevance. This longitudinal population-based cohort study by Paul and coworkers addresses this important issue. The authors have genotyped 23 SNPs in 285 PD patients. Genome-wide independent and significant association with PD risk was observed for each of these 23 SNPs in a previously reported GWAS meta-analysis (Nalls et al., 2014). Subsequently, the authors have calculated a polygenic risk score for each patient (using the number of risk alleles and the effect size of each risk allele, based on the GWAS meta-analysis). The polygenic risk score was significantly associated with a more rapid decline of the Mini-Mental State Examination (MMSE). Additionally, significant association of the polygenic risk score with a faster progression of motor symptoms to Hoehn-and-Yahr stage 3 (HY stage 3) was observed. HY stage 3 defines the appearance of balance problems and is an important disease milestone in PD. Faster progression to HY stage 3 was also shown to be significantly associated with a polygenic score (calculation based on 19 GWAS SNPs) in a Norwegian longitudinal study with mean follow-up duration of more than 10 years (Pihlstrom et al., 2016).

Paul and coworkers highlight the influence of common genetic variants and of the polygenic architecture on the variability of disease progression rate in PD. These findings need to be replicated in studies with larger sample size and longer follow-up duration. Careful clinical characterization and periodic standardized clinical follow-up is mandatory for the accuracy of the phenotypical data in these studies. The development and validation of biomarkers to track the disease progression in PD patients will hopefully contribute to the identification of novel genetic determinants in future studies.